***** H2 - Parents hypothesis - PID - binary

* Produce Table 1 in Appendix M - Parents hypothesis controlling for incumbent partisanship (binary) 

		clear all
		
		cd "${data}"	
		
		use data_ess.dta, clear	
		
				* Define significance stars
		graph set window fontface "Arial Narrow"
		global stars "+ 0.10 * 0.05 ** 0.01 *** 0.001"
		
				* Declare survey design for dataset
		svyset, clear 
		svyset country_code [weight=pspwght], strata(essround)
		
						
		eststo clear
		
		eststo m1: svy: reg stfeco  b0.dummy1834 agea income b0.unemployed education b0.incumbent_dummy i.essround i.country_code if agea>34 // restricted sample

		eststo Economy: svy: reg stfeco b0.dummy1834 agea income b0.unemployed education b0.incumbent_dummy unemployment_rate i.essround i.country_code if agea>34 // restricted sample

		eststo m3: svy: reg stfgov  b0.dummy1834 agea income b0.unemployed education b0.incumbent_dummy i.essround i.country_code if agea>34 // restricted sample
			
		eststo Government: svy: reg stfgov b0.dummy1834 agea income b0.unemployed education b0.incumbent_dummy unemployment_rate i.essround i.country_code  if agea>34  // restricted sample

		
	esttab m1 Economy m3 Government using ${tables}/appendixM.tex, ///
			nomtitles booktabs replace ///
			indicate("Country FE = *.country_code" "Year FE = *.essround", labels("\checkmark" "")) ///
			stats(N r2, fmt(%9.0fc %9.2fc) labels("Observations" "R-squared")) ///
			nobaselevels substitute("=1" "") nogap compress nonotes b(2) se(2) starlevels( ${stars}) label mlabels("Model 1" "Model 2" "Model 3" "Model 4" ) 
